20768: Developing SQL 2016 Data Models Training & Certification Course
Overview
SQL Data Models Course 20768-C: Overview
SpireTec, the leading IT and management training service provider, offers instructor-led online classroom training on developing data models using SQL. We help you prepare for the Exam 70-768 in a step-by-step manner.
Learn how to implement both multidimensional and tabular data models and how to create cubes, dimensions, measures, and measure groups. Acquire skills for developing SQL Data Models in all formats as follows:
- Conceptual Data Models: High-level, static business structures and concepts
- Logical Data Models: Entity types, data attributes and relationships between entities
- Physical Data Models: The internal schema database design
Organizations – for-profit, non-profit or government – everyone is trying to make the most of the data they generate. It helps them improve their products and services and gain operational excellence. It’s easier said than done. Here comes the need of developing data models that can make it easy to organize and comprehend data and get answers to queries and stay relevant to the emerging demands or situations.
Developing Data Models: Exam 20768-C Syllabus
- Describe the components, architecture, and nature of a BI solution
- Create a multidimensional database with Analysis Services
- Implement dimensions in a cube
- Implement measures and measure groups in a cube
- Use MDX syntax
- Customize a cube
- Implement a tabular database
- Use DAX to query a tabular model
- Use data mining for predictive analysis
Who Should Learn Developing Data Models?
BI Developers
Nowadays, organizations hire data engineers for developing scalable BI (Business Intelligence) solutions with minimal / zero downtime. Developing data models that can comprehend data qualitatively and quantitatively with a rapid rate is the need of the hour. Knowledge and experience with data warehouse design and data modeling principles help candidates to perform their jobs effortlessly.
Data Scientists
Developing efficient data models, data scientists can add value to the work they do. The models help them apply advanced statistical and machine learning algorithms on large scale multidimensional data and generate results that will be leveraged by the business teams.
Prerequisites for 20768-C certification
Experience of querying relational databases using Transact-SQL, which is Microsoft’s and Sybase’s proprietary extension to the SQL (Structured Query Language).
Recommended course
Full Description
Module 1: Introduction to Business Intelligence and Data Modelling
This module introduces key BI concepts and the Microsoft BI product suite.
Lessons
- Introduction to Business Intelligence
- The Microsoft business intelligence platform
Lab: Exploring a BI Solution
- Exploring a Data Warehouse
- Exploring a data model
After completing this module, students will be able to:
- Describe BI scenarios, trends, and project roles.
- Describe the products that make up the Microsoft BI platform.
Module 2: Creating Multidimensional Databases
This module describes how to create multidimensional databases using SQL Server Analysis Services.
Lessons
- Introduction to Multidimensional Analysis
- Data Sources and Data Source Views
- Cubes
- Overview of Cube Security
- Configure SSAS Monitoring SSAS
Lab: Creating a multidimensional database
- Creating a Data Source
- Creating and Configuring a data Source View
- Creating and Configuring a Cube
- Adding a Dimension to a Cube
After completing this module, you will be able to:
- Describe considerations for a multidimensional database.
- Create data sources and data source views.
- Create a cube
- Implement security in a multidimensional database.
- Configure SSAS to meet requirements including memory limits, NUMA and disk layout.
- Monitor SSAS performance.
Module 3: Working with Cubes and Dimensions
This module describes how to implement dimensions in a cube.
Lessons
- Configuring Dimensions
- Defining Attribute Hierarchies
- Implementing Sorting and Grouping Attributes
- Slowly Changing Dimensions
Lab: Working with Cubes and Dimensions
- Configuring Dimensions
- Defining Relationships and Hierarchies
- Sorting and Grouping Dimension Attributes
After completing this module, you will be able to:
- Configure dimensions.
- Define attribute hierarchies.
- Implement sorting and grouping for attributes.
- Implement slowly changing dimensions.
Module 4: Working with Measures and Measure Groups
This module describes how to implement measures and measure groups in a cube.
Lessons
- Working with Measures
- Working with Measure Groups
Lab: Configuring Measures and Measure Groups
- Configuring Measures
- Defining Regular Relationships
- Configuring Measure Group Storage
After completing this module, you will be able to:
- Configure measures.
- Configure measure groups.
Module 5: Introduction to MDX
This module describes the MDX syntax and how to use MDX.
Lessons
- MDX fundamental
- Adding Calculations to a Cube
- Using MDX to Query a Cube
Lab: Using MDX
- Querying a cube using MDX
- Adding a Calculated Member
After completing this module, you will be able to:
- Use basic MDX functions.
- Use MDX to add calculations to a cube.
- Use MDX to query a cube.
Module 6: Customizing Cube Functionality
This module describes how to customize a cube.
Lessons
- Implementing Key Performance Indicators
- Implementing Actions
- Implementing Perspectives
- Implementing Translations
Lab : Customizing a Cube
- Implementing an action
- Implementing a perspective
- Implementing a translation
After completing this module, you will be able to:
- Implement KPIs in a Multidimensional database
- Implement Actions in a Multidimensional database
- Implement perspectives in a Multidimensional database
- Implement translations in a Multidimensional database
Module 7: Implementing a Tabular Data Model by Using Analysis Services
This module describes how to implement a tabular data model in Power Pivot.
Lessons
- Introduction to Tabular Data Models
- Creating a Tabular Data Model
- Using an Analysis Services Tabular Data Model in an Enterprise BI Solution
Lab : Working with an Analysis Services Tabular Data Model
Creating an Analysis Services Tabular Data Model
Configure Relationships and Attributes
Configuring Data Model for an Enterprise BI Solution.
After completing this module, students will be able to:
- Describe tabular data models
- Describe how to create a tabular data model
- Use an Analysis Services Tabular Model in an enterprise BI solution
Module 8: Introduction to Data Analysis Expression (DAX)
This module describes how to use DAX to create measures and calculated columns in a tabular data model.
Lessons
- DAX Fundamentals
- Using DAX to Create Calculated Columns and Measures in a Tabular Data Model
Lab: Creating Calculated Columns and Measures by using DAX
- Creating Calculated Columns
- Creating Measures
- Creating a KPI
- Creating a Parents Child Hierarchy
After completing this module, students will be able to:
- Describe the key features of DAX
- Create calculated columns and measures by using DAX
Module 9: Performing Predictive Analysis with Data Mining
This module describes how to use data mining for predictive analysis.
Lessons
- Overview of Data Mining
- Creating a Custom Data Mining Solution
- Validating a Data Mining Model
- Connecting to and Consuming a Data-Mining Model
- Using the Data Mining add-in for Excel
Lab: Using Data Mining
- Creating a Data Mining Structure and Model
- Exploring Data Mining Models
- Validating Data Mining Models
- Consuming a Data Mining Model
- Using the Excel Data Mining add-in
Fees & Schedule
Delivery Mode | Course Duration | Fees |
---|---|---|
Live Virtual Training | 3 Days | Ask for Quote |
Onsite Classroom Training | 3 Days | Ask for Quote |
Customized Training | 3 Days | Ask for Quote |